For much of the past decade, the quantum industry has been defined by scientific progress. Researchers have steadily improved qubit quality, reduced error rates, and demonstrated increasingly sophisticated capabilities across quantum computing, sensing, and communications. Hardware roadmaps continue to push technical boundaries, while quantum sensing demonstrators are set to deliver unprecedented detection, navigation performances.
Today, leading quantum hardware roadmaps place as much emphasis on fault tolerance, error correction, and hybrid quantum-classical architectures as they do on hardware performance. The industry’s attention is moving towards a harder challenge: engineering quantum technologies into systems that organisations can trust, integrate, and deploy.
Scientific discovery remains fundamental, but commercial success will increasingly depend on what happens after the laboratory.
The first quantum advantage will solve specific operational problems
As quantum technologies mature, the earliest value is unlikely to come from replacing classical computing altogether. Instead, quantum is likely to deliver its earliest impact in carefully defined operational problems where conventional approaches face fundamental limitations.
For example, quantum sensing offers opportunities to improve precision beyond classical limits; secure quantum communications promise stronger protection of critical information; and advances in position, navigation, and timing with quantum technologies could improve resilience where satellite navigation is unavailable or compromised. The real test is not whether quantum can demonstrate performance, but whether it can solve a practical problem better than the tools already in use.
This is also changing how many organisations approach quantum development. Many research teams now begin with the operational challenge itself, asking whether quantum can solve a real-world problem with enough improvement to justify adoption. Proofs of concept then become a way to evaluate both performance gains and practical constraints. Verification frameworks will also become an important aspect of moving quantum technologies from an experimental novelty to a safe, reliable, and deployable reality.
Future operational systems are also unlikely to be purely quantum. Quantum and classical technologies will work alongside one another, each performing the tasks they are best suited for. Success will depend on integrating quantum capabilities into larger operational architectures rather than treating them as standalone technologies.
That means the next wave of quantum capability will depend on systems engineering as much as physics.
A hybrid quantum workforce will look very different
As quantum technologies move closer to deployment, multidisciplinary engineering becomes just as important as scientific discovery. Future teams will need to combine expertise in quantum algorithms, software engineering, systems integration, cybersecurity, and operational domains. Engineers must understand not only how quantum technologies function, but also how they interact with existing infrastructure, software stacks, and operational workflows. They must be capable of looking at a highly complex, classical problem and natively formatting it into quantum logic to achieve actual, reproducible, and trustworthy quantum advantage.
Scientific breakthroughs may originate inside laboratories, but operational deployment depends on people capable of translating those breakthroughs into systems that function consistently under real-world conditions.
Collaboration therefore becomes an engineering requirement rather than simply a research objective. Universities, startups, government agencies, and industry each contribute different capabilities to the deployment challenge. Scientific research advances fundamental understanding. Engineers translate discoveries into systems. Operational users define the requirements that ultimately determine whether a technology delivers value.
The organisations that succeed are increasingly those that can bring these disciplines together rather than optimise each independently.
Trust is becoming quantum’s defining challenge
If hybrid systems represent the technical challenge, trust represents the operational one.
As quantum technologies move beyond the lab, organisations will ask the same questions being posed about AI today. How do we properly validate and qualify functionalities of quantum systems and subsystems? How should organisations decide whether one approach is suitable for operational deployment while another is not?
These questions explain why benchmarking and standards are becoming increasingly important across the quantum ecosystem.
Initiatives such as the Benchmarking Alliance for Quantum Computing (BACQ), which brings together research and industry participants to develop application-oriented benchmarks, reflect growing recognition that evaluating hardware performance alone will not be enough. Similarly, international standards initiatives, including ongoing work within IEEE, signal that the industry is beginning to converge around common approaches for evaluating quantum technologies beyond laboratory demonstrations.
This represents an important shift in priorities. Measuring qubit counts or experimental performance remains valuable, but future users will need the trust and confidence that quantum systems solve practical problems reliably, consistently, and under realistic operating conditions. In critical environments, that confidence is not optional.
Quantum’s next phase will be built through ecosystems
Governments are treating quantum as a strategic investment, but the real shift is from policy to implementation. Singapore is a clear example. The Economic Strategy Review Final Report identifies quantum as one of the country’s future growth technologies, while the National Quantum Office coordinates the National Quantum Strategy across research, innovation, enterprise, partnerships and talent. That policy direction is now showing up in practice, including the DIS and DSTA collaboration with IBM to explore quantum computing for mission planning and logistics optimisation.
That same pattern is emerging elsewhere. Japan is strengthening collaboration between research institutions and industry through its quantum future society vision, while South Korea has identified quantum as one of ten national strategic tech areas. Beyond APAC, Europe is taking a similar ecosystem approach through initiatives such as the EU Quantum Flagship, which brings together research, industry and policymakers to accelerate commercialisation.
This matters because quantum deployment does not happen in isolation. It advances faster when research can be tested against operational needs, when engineers can work alongside domain specialists and when public and private institutions align around use cases, not theory alone.
Singapore and APAC are especially relevant because Thales already has the footprint, partnerships and systems capability to bridge research and deployment. In Singapore, Thales has over 2,000 employees across four locations, with deep R&D and industrial activity, plus partnerships with CAAS, HTX, DSTA, NTU and the wider ecosystem. That makes the region a credible place to test how quantum moves from research into operational use.
The laboratories have already shown what quantum can do. The real test now is whether governments, industry and research partners can turn that progress into systems that are trusted, deployable and useful at scale. Quantum’s next breakthrough will not be a single scientific milestone. It will be the moment the technology becomes operational reality.
